1. Cell Biology
  2. Computational and Systems Biology
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Integrating images from multiple microscopy screens reveals diverse patterns of protein subcellular localization change

Research Article
  • Cited 9
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Cite this article as: eLife 2018;7:e31872 doi: 10.7554/eLife.31872

Abstract

Evaluating protein localization changes on a systematic level is a powerful tool for understanding how cells respond to environmental, chemical, or genetic perturbations. To date, work in understanding these proteomic responses through high-throughput imaging has catalogued localization changes independently for each perturbation. To distinguish changes that are targeted responses to the specific perturbation and more generalized programs, we developed a scalable approach to visualize the localization behavior of proteins across multiple experiments as a quantitative pattern. By applying this approach to 24 experimental screens consisting of nearly 400,000 images, we differentiate specific responses from more generalized ones, discover nuance in the localization behavior of stress-responsive proteins, and form hypotheses by clustering proteins with similar patterns. While previous approaches aim to capture all localization changes for a single screen as accurately as possible, our work aims to integrate large amounts of imaging data to find unexpected new cell biology.

Article and author information

Author details

  1. Alex X Lu

    Department of Computer Science, University of Toronto, Toronto, Canada
    Competing interests
    The authors declare that no competing interests exist.
  2. Yolanda T Chong

    Terrence Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Canada
    Competing interests
    The authors declare that no competing interests exist.
  3. Ian Shen Hsu

    Department of Cell and Systems Biology, University of Toronto, Toronto, Canada
    Competing interests
    The authors declare that no competing interests exist.
  4. Bob Strome

    Department of Cell and Systems Biology, University of Toronto, Toronto, Canada
    Competing interests
    The authors declare that no competing interests exist.
  5. Louis-Francois Handfield

    Department of Computer Science, University of Toronto, Toronto, Canada
    Competing interests
    The authors declare that no competing interests exist.
  6. Oren Kraus

    Department of Electrical and Computer Engineering, University of Toronto, Toronto, Canada
    Competing interests
    The authors declare that no competing interests exist.
  7. Brenda J Andrews

    Terrence Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Canada
    Competing interests
    The authors declare that no competing interests exist.
  8. Alan M Moses

    Department of Computer Science, University of Toronto, Toronto, Canada
    For correspondence
    alan.moses@utoronto.ca
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3118-3121

Funding

National Science and Engineering Research Council (Pre-Doctoral Award)

  • Alex X Lu

Canada Research Chairs (Tier II Chair)

  • Alan M Moses

Canada Foundation for Innovation

  • Brenda J Andrews
  • Alan M Moses

Canadian Institutes of Health Research (FDN-143265)

  • Brenda J Andrews

Canadian Institute for Advanced Research (Senior Fellow)

  • Brenda J Andrews

Canadian Institutes of Health Research (MOP-97939)

  • Brenda J Andrews

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Emmanuel Levy, Weizmann Institute of Science, Israel

Publication history

  1. Received: September 10, 2017
  2. Accepted: March 30, 2018
  3. Accepted Manuscript published: April 5, 2018 (version 1)
  4. Version of Record published: May 4, 2018 (version 2)
  5. Version of Record updated: October 11, 2018 (version 3)

Copyright

© 2018, Lu et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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